An Introduction to Statistical Signal Processing
by R. M. Gray, L. D. Davisson
Publisher: Cambridge University Press 2005
ISBN/ASIN: 0521838606
ISBN-13: 9780521838603
Number of pages: 478
Description:
This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book.
Download or read it online for free here:
Download link
(2.9MB, PDF)
Similar books
Signal Processingby Sebastian Miron - InTech
The exponential development of computer power over the last few decades, transformed signal processing in an essential tool for a wide range of domains such as telecommunications. This book provides highlights of the current research in the area.
(13020 views)
Fourier Transform - Signal Processingby Salih Mohammed Salih - InTech
This book focuses on the Fourier transform applications in signal processing techniques. Topics covered: DFT, FFT, OFDM, estimation techniques and the image processing techniques. Written for electrical engineers, communication engineers, etc.
(10875 views)
Concise Signal Modelsby Michael Wakin - Connexions
This book reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, etc.
(9500 views)
Statistical Spectral Analysis: A Non-Probabilistic Theoryby William A. Gardner - Prentice Hall
This book is intended to serve as both a graduate-level textbook and a technical reference. The focus is on fundamental concepts, analytical techniques, and basic empirical methods. The only prerequisite is an introductory course on Fourier analysis.
(9526 views)